The location and layout of urban charging stations based on differential competing-species model
Wang Meichen1, Yang Ruolin1, Xi Dianbing2, Sun Xinyu1
1. School of Information Engineering, Nanchang University, Nangchang 330031; 2. School of Materials Science and Engineering, Nanchang University, Nangchang 330031
Abstract：With the environmental protection consciousness of people increasing, government policy encouraging, electric vehicles certainly will become more and more popular in the future, and the location and layout of charging station become very important.In this paper, by analyzing the relationship between the number of electric vehicles and the number of traditional fuel vehicles, competing-species model is put forward. On the basis of this prediction model, the optimal number of building charging stations is obtained through integer programming, and the charging station address is determined near the charging demand point. According to sites selection, Voronoi diagram is drawn to obtain the range of service of each charging station. Case analysis verifies the practicability and feasibility of this model.
王美晨, 杨若琳, 席典兵, 孙新宇. 基于种群竞争预测模型下的城市充电站选址与布局[J]. 电气技术, 2019, 20(2): 18-22.
Wang Meichen, Yang Ruolin, Xi Dianbing, Sun Xinyu. The location and layout of urban charging stations based on differential competing-species model. Electrical Engineering, 2019, 20(2): 18-22.
[1] SongY H, Yang X, Lu Z X, et a1. Integration of plug in hybrid and electric vehicles: experience from China[C]// Proceedings of IEEE Power & Energy Society Genral Meeting, Minneapolis, MN, USA, 2010, 7: 1-5. [2] Ferdowsi M.Vehicle fleet as a distributed energy storage system for the power[C]//Proceedings of IEEE Power & Energy Society General Meeting. Catgary, Canada, 2009, 7: 1-2. [3] 高赐威, 张亮. 电动汽车充电对电网影响的综述[J]. 电网技术, 2011, 35(2): 127-131. [4] Weiss M, Patel M K, Junginger M, et al.On the electrification of road transport-learning rates and price forecasts for hybrid-electric and battery-electric vehicles[J]. Energy Policy, 2012, 48: 374-393. [5] 赵书强, 李志伟, 党磊. 基于城市交通网络信息的电动汽车充电站最优选址和定容[J]. 电力自动化设备, 2016, 36(10): 8-15, 23. [6] Liu Zhipeng, Wen Fushuan, Ledwich G.Optimal planning of electric-vehicle charging stations in distribution systems[J]. IEEE Transactions on Power Delivery, 2013, 28(1): 102-110. [7] 舒隽, 唐刚, 韩冰. 电动汽车充电站最优规划的两阶段方法[J]. 电工技术学报, 2017, 32(3): 10-17. [8] 程宏波, 肖永乐, 王勋, 等. 基于引力模型的电动汽车充电站选址规划[J]. 电工电能新技术, 2016, 5(5): 61-66. [9] 李菱, 李燕青, 姚玉海, 等. 基于遗传算法的电动汽车充电站的布局规划[J]. 华东电力, 2011, 39(6): 1004-1006. [10] Brackett-Rozinskyn B, Wilton K, Altieri J.Mobile to mobil: the primary energy costs for cellular and landline telephones[J]. The UMAP, 2009, 30(3): 313-332. [11] 李骄, 许彦红, 吉灵波. 基于Matlab的秃杉种群竞争数学模型仿真分析[J]. 江苏农业科学, 2014, 42(7): 175-178. [12] 司守奎, 孙兆亮. 数学建模算法与应用[M]. 2版. 北京: 国防工业出版社, 2016. [13] 王丛佼, 王锡淮, 陈国初, 等. 基于改进差分进化算法的潮流发电机组微观选址[J]. 电工技术学报, 2016, 31(15): 99-108. [14] Liu Z F, Zhang W, Ji X, et a1. Optimal planning of charging station for electric vehicle based on particle swarm optimization[C]//Proceedings of IEEE Innova- tive Smart Grid Technologies-Asia, Tianjin, 2012, 5: 21-24. [15] 陈连福. 电动出租车充电站布局规划研究[D]. 北京: 北京交通大学, 2015. [16] 郭国太. 电动汽车充电站建设可行性分析[J]. 电气技术, 2017, 18(3): 120-124. [17] 路欣怡, 刘念, 陈征, 等. 电动汽车光伏充电站的多目标优化调度方法[J]. 电工技术学报, 2014, 29(8): 46-56. [18] 徐武峰. 电动汽车充换电设施投资效益分析[J]. 电气技术, 2015, 16(4): 108-111, 114. [19] 肖波. 电动汽车充电站规划研究[D]. 长沙: 湖南大学, 2014.
2019, Vol. 20 
